To train models for music generation tasks using Julia, you can leverage Flux.jl for deep learning and MIDI libraries like MIDI.jl for handling musical data. Here is the code snippet you can refer to:
In the above code, we are using the following steps:
- MIDI Preprocessing: Load MIDI files and extract notes or sequences as numerical data.
- Model Definition: Use an RNN or LSTM for sequence modeling.
- Training: Train the model to predict the next note in a sequence.
- Music Generation: Use the trained model to generate a sequence of notes.
- Output MIDI: Save generated sequences as a MIDI file for playback.
Hence, this approach provides a framework for building music generation models and handling MIDI data efficiently in Julia.